Precipitation

(data through 7/18/12)
Data Source(s): High Plains Regional Climate Center

Dry conditions since January 1 have finally dominated the water year signal, canceling out the wet weather of November and December. Across most of Arizona and New Mexico, precipitation has been below average since the water year began on October 1 (Figures 2a–b). Only a few isolated areas have above-average precipitation totals; a single winter storm and early monsoon activity delivered 130–200 percent of average precipitation to western Pima County and copious precipitation to northwest New Mexico. The Colorado Plateau has seen considerable variability in precipitation. Infrequent storms left part of the Navajo Nation dry while pelting adjacent areas with more rain and snow. Central Mohave County in northwest Arizona also benefitted from several winter storms.

In the past 30 days, monsoon activity created wetter-than-average conditions along the lower Colorado River valley between Arizona and California and extremely wet conditions in most of southern Arizona (Figures 2c–d). Eastern New Mexico remains in a monsoon void, as the high-pressure ridge often has remained too far to the west to pull moisture from Mexico into that region. Southwestern New Mexico also has missed out on the monsoon, which normally tracks through the southern border of the two states.

Notes:

The water year begins on October 1 and ends on September 30 of the following year. As of October 1, 2011, we are in the 2012 water year. The water year is a more hydrologically sound measure of climate and hydrological activity than is the standard calendar year.

Average refers to the arithmetic mean of annual data from 1971–2000. Percent of average precipitation is calculated by taking the ratio of current to average precipitation and multiplying by 100.

The continuous color maps (Figures 2a, 2c) are derived by taking measurements at individual meteorological stations and mathematically interpolating (estimating) values between known data points. Interpolation procedures can cause aberrant values in data-sparse regions.

The dots in Figures 2b and 2d show data values for individual meteorological stations.